libs/transformer/open_ai_whisper.py

import torch
from transformers import AutoModelForSpeechSeq2Seq, AutoProcessor, pipeline


def open_ai_whisper_api(url: str):
    device = "cuda:0" if torch.cuda.is_available() else "cpu"
    torch_dtype = torch.float16 if torch.cuda.is_available() else torch.float32

    model_id = "openai/whisper-large-v3-turbo"

    model = AutoModelForSpeechSeq2Seq.from_pretrained(
        model_id, torch_dtype=torch_dtype, low_cpu_mem_usage=True, use_safetensors=True
    )
    model.to(device)

    processor = AutoProcessor.from_pretrained(model_id)

    pipe = pipeline(
        "automatic-speech-recognition",
        model=model,
        tokenizer=processor.tokenizer,
        feature_extractor=processor.feature_extractor,
        torch_dtype=torch_dtype,
        device=device,
        return_timestamps=True,
    )

    generate_kwargs = {
    "return_timestamps": True,
    "language": "english"
    }


    result = pipe(url, generate_kwargs=generate_kwargs)
    print('vao day')
    return result.get('text'), result.get('chunks')